Yesterday a total beginner posted their first web app, and honestly, it’s got more prompt tooling packed in than half the paid products out there. u/seraphym1389 taught themselves web dev and AI tooling from scratch, then built Context CikaDule: a context engineering console for crafting prompts across GPT-4, Claude, Gemini, and local models.
Here’s the twist. This isn’t a wrapper that spits out one templated prompt and calls it a day. It’s got four build modes (Quick, Guided, Raw, Templates), auto-formats output per model family, and includes an Arena mode that runs two models side by side on the same prompt so you can actually see the divergence in outputs. A beginner’s “learning project” accidentally built the A/B testing layer most prompt tools skip entirely.
The real sleeper feature is the Prompt Quality Linter. It scores your prompt live across five criteria: task clarity, role, constraints, format, and context. That’s the kind of feedback loop that turns “write me a better prompt” from guesswork into something measurable.
How to actually use it
- 🎯 Start in Guided mode and fill the 16 fields (role, task, constraints, edge cases, the works) for anything that actually matters.
- 🔍 Run it through the Linter before you send it anywhere. Fix whatever drags your score down.
- ⚔️ Drop it into Arena mode and compare Claude vs GPT output on the identical prompt.
- 🧩 If you’ve got an old prompt lying around, paste it into auto-detect and let it guess the closest template as a starting structure.
- 🚀 Export the model-formatted version and ship it into your actual workflow.
Pro tip: Treat the Arena mode as your cheapest eval harness. Before you commit to a model for a workflow, run three or four real prompts through it side by side. You’ll catch formatting quirks (Claude wants different delimiters than GPT) before they cost you a failed production run.
Second pro tip: The linter score is a floor, not a ceiling. A perfect 5/5 just means your prompt is well-structured, not that it’s good for your specific task. Use it to catch obvious gaps, not to declare victory.
Worth is genuinely a fair ask here, not for the app being flawless (it isn’t, the builder says so themselves), but for the instinct: build the thing you wish existed while you’re still learning. Go poke at the live app, break something, and leave a comment telling them what broke.
[Begginer project looking for feedback]: I have created Prompt Engineering console trough learning as my first project version 1.0 Want to hear oppinions from experienced people
by u/seraphym1389 in PromptEngineering